It's easy to see how the ability to predict the future accurately could be a game-changer for many businesses. Of course, predicting the future with 100% certainty is impossible. However, there are plenty of simple situations that can help us to predict with a high degree of accuracy, and still, more when we can determine how likely something is to occur.
The old adage 'the best predictor of the future is the past' is one that businesses should remember when making plans for the future. By continually gathering as much useful data as possible, businesses can always rely on past data and analytics to assess current situations and predict what the future holds.
Why are predictive analytics important?
Predictive analytics uses data about the past and present to determine what is likely to occur in the future. Data-driven decision making is commonplace in just about every industry today, and predictive analytics is one of several approaches businesses use to enhance decision-making processes and improve operational efficiencies.
For example, predictive analytics are used throughout the financial services industry to improve pattern detection, which can be used to flag suspicious transactions or even make decisions about loan applications. In the same way, manufacturing businesses can use this approach to predict when equipment is likely to fail or require maintenance, or forecast material requirements, enabling you to plan operations accordingly. For any business, predictive analytics are useful for assessing progress and business operations as a whole.
What types of forecasting does predictive analytics enable?
Using predictive analytics enables your business to make a number of forecasts:
This predicts the volume, and types, of orders expected over a certain period of time, enabling you to understand what products and services you are likely to sell during that period and how much stock you will need to meet demand
Financial or accounting forecasting
Aims to predict future income and expenditure, enabling you to track your likely trajectory and budgets accordingly
Supply chain forecasting
Predicts the likely journey times and probable arrival dates for goods travelling through the supply chain
Outlines likely sales volumes of specific products and services or overall sales figures for the entire business. Sales forecasting is useful in anticipating future resource requirements and cash flow
How can ERP help you with predictive machine maintenance?
Manufacturing businesses know that unexpected equipment failures can be disastrous, and set off a chain reactions with costly consequences. While there will always be a chance that any piece of equipment will fail unexpectedly, you can work to minimise this chance through regular maintenance schedules. Using predictive analytics, your manufacturing operation can put in place predictive triggers that action maintenance or plan machine shutdowns in quiet periods.
Often these are based on demand, or on the operating capacities allowed before checks to ensure your machines continue to run as expected must be undertaken. Resources can be focused, and disruption minimised in an integrated system where live data or forecasts are utilised to inform these decisions.
ERP solutions enable manufacturers, like you, to gather and analyse the data you need to make the predictive approach to machine maintenance work. For example, by recording the frequency and duration of equipment repairs, ERP systems can identify common problems and potential solutions, as well as anticipating when downtime is likely to occur and reallocate resources accordingly.
In using historical and real-time data in parallel you can work to improve operational efficiency, cost-effectiveness and forward plan to optimise the best way forward.
WinMan manufacturing ERP software solutions are a flexible and robust solution for manufacturers looking to refine lean manufacturing processes or consolidate existing systems.
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